二滩拱坝垂线观测系统

介绍了二滩拱坝垂线孔的造孔、保护管的安装及其检测情况 ,以及垂线系统的安装和运行、观测成果计算和资料分析。

Landscape change detection in Yulin prefecture

Landscape is a dynamic phenomenon that almost continuously changes. The overall change of a landscape is the result of complex and interacting natural and spontaneous processes and planned actions by man. However, numerous activities by a large number of individuals are not concerted and contribute to the autonomous evolution of the landscape in a similar way as natural processes do. There is a well-established need to detect land use and ecological change so that appropriate policies for the regional sustainable development can be developed. Landscape change detection is considered to be effectively repeated surveillance and needs especially strict protocols to identify landscape change. This paper developed a series of technical frameworks on landscape detection based on Landsat Thematic Mapper (TM) Data. Through human-machine interactive interpretation, the interpretation precision was 92.00% in 1986 and 89.73% in 2000. Based on the interpretation results of TM images and taking Yulin prefecture as a case study area, the area of main landscape types was summarized respectively in 1986 and 2000. The landscape pattern changes in Yulin could be divided into ten types.

Preliminary Study on Simulation of Global Seismic Activities with Global Strain Rate

The relationship between the strain rate field observed by GPS and global distribution of strong earthquakes is analyzed in this work. How do we recognize the characteristics of global seismic activities with space observation technology? A preliminary model of Cellular Automata that could simulate the global seismic activities both in time and space has been established based on the results of global strain rate field provided by the GSRM Program. The grid of the model is evenly divided,which is consistent with that of GSRM.The status of each cell is its strain state,and is adjusted according to the evolution rules.Maximum shear strain criterion is adopted in the evolution of the Cellular Automata. The threshold for cells in surface expansion is 80% of that for those in compression. The preliminary model could in general simulate the main characteristics of the distribution of the global seismic activities. It could exhibit in general the global distribution of weak and active tectonic activities. Although the preliminary Cellular Automata model needs to be improved in many aspects,the result suggests the possibility of modeling the general features of rather complicated global seismic activities based on the strain rates obtained by GPS and other observations.

Influence and Local Influence for Explained Variation in Survival Analysis

The amount of explained variation R2 is an overall measure used to quantify the information in a model and especially how useful the model might be when predicting future observations, explained variation is useful in guiding model choice for all types of predictive regression models, including linear and generalized linear models and survival analysis. In this work we consider how individual observations in a data set can influence the value of various R2 measures proposed for survival analysis including local influence to assess mathematically the effect of small changes. We discuss methodologies for assessing influence on Graf et al.＇s R2G measure, Harrell＇s C-index and Nagelkerke＇s R2N. The ideas are illustrated on data on 1391 patients diagnosed with Diffuse Large B-cell Lymphoma （DLBCL）, a major subtype ofNon-Hodgkin＇s Lymphoma （NHL）.

专题讲座 动态变形分析 第二讲 ARMA模型的识别

2.1 时间序列的动态特性 2.1.1 格林函数G 由式(1—12)可写成 x_t=(θ(B))/(φ(B))a_t将θ(B)/φ(B)作长除法,得 x_t=(1+G_1B+G_2B^2+…)α_t顾及K步线性推移算子B^k。

ON ASYMPTOTIC NORMALITY OF PARAMETERS IN LINEAR EV MODEL

This paper studies the parameter estimation of one dimensional linear errors-in-variables(EV) models in the case that replicated observations are available in some experimental points.Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in construction of large-sample confidence regions.

An effective genetic algorithm to VDA with discontinuous “on-off” switches

With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of describing the at-mospheric or oceanic movement more precisely,and on the other hand,introduces non-smoothness in the form of "on-off" switches into the models."On-off" switches enhance the nonlinearity of the models and finally result in the loss of the effec-tiveness of variational data assimilation(VDA) based on the conventional adjoint method(ADJ).This study,in virtue of the optimization ability of a genetic algorithm(GA) for non-smooth problems,presents a new GA(referred to as GA NEW) to solve the problems of the VDA with discontinuous "on-off" processes.In the GA-NEW,adaptive selection and mutation oper-ators,blend crossover operator,and elitist strategy are combined in application.In order to verify the effectiveness and feasi-bility of the GA NEW in VDA,an idealized model of partial differential equation with discontinuous "on-off" switches in the forcing term is adopted as the governing equation.By comparison with the ADJ,it is shown that the GA NEW in VDA is more effective and can yield better assimilation retrievals.In addition,VDA experiments demonstrate that the performance of a GA is greatly related to the configuration of genetic operators(selection,crossover and mutation operators) and much better results may be attained with more proper genetic operations.Furthermore,the robustness of the GA NEW to observational noise,model errors and observation density is investigated,and the results show that the GA NEW has stronger robustness than the ADJ with respect to all the three observation noises,model errors,and sparse observation.